The underactuation of conventional aerial vehicles limits their ability to independently control position and attitude, motivating the use of overactuated designs such as tilt-rotor quadrotors. Existing works on tilt-rotor quadrotors primarily focus on determining the minimum thrust-to-weight ratio required for hovering at arbitrary orientations. However, they do not address the maximum allowable attitude range within which independent control is feasible given specific thrust constraints. In this work, we investigate the feasible attitude range within which a tilt-rotor quadrotor can maintain independent control, given rotor thrust limits. First, we formulate the thrust constraints as convex functions and solve them using convex optimization techniques to identify feasible sets. To determine the maximum attitude that allows for independent control under thrust constraints, we pose a nonconvex optimization problem and employ a successive convex approximation (SCA) technique to compute a optimal solution, which corresponds to the optimal solution of the original nonconvex problem. Given the maximum attitude limits, we then compute the minimum thrust required per rotor to achieve independent control. Furthermore, we determine the maximum allowable disturbance magnitude that the tilt-rotor quadrotor can handle while retaining independent control. The study results are verified through processor-in-the-loop (PIL) simulations and outdoor hardware experiments on a tilt-rotor quadrotor. An illustrative video showing both the PIL simulation and hardware experimental results can be found at: https://youtu.be/6qjc9_KtACM Note to Practitioners—This paper is motivated by the potential application of tilt-quadrotors in inspection, search and rescue, and aerial manipulation, owing to their ability to perform agile maneuvers in confined environments. However, ensuring independent control of both position and attitude across all orientations remains a practical challenge, primarily...

This article presents an experimental demonstration of an attitude-constrained adaptive guidance and control framework for safe autonomous docking, evaluated using a planar floating satellite platform testbed. The proposed approach combines a jerk-minimizing explicit guidance law, which enforces terminal constraints on position, velocity, and acceleration, with an adaptive tracking controller designed to handle modeling uncertainties, actuator limitations, and external disturbances. The guidance strategy generates a smooth, real-time trajectory for the chaser satellite, ensuring compatibility with limited onboard computation and maintaining high terminal accuracy. To ensure safe operation throughout the docking maneuver, a barrier-Lyapunov-based adaptive controller is augmented that imposes state constraints to enforce strict adherence to the desired trajectory with predefined nominal bounds. By virtue of the constraint, the tracking error is bounded within a pre-defined bound. The bound is not time-varying because the reference trajectory is designed to begin from the current state of the robot with minimum jerk. The complete framework is demonstrated through hardware-in-the-loop experiments using a planar floating satellite platform and a prototype docking station. Experimental results corroborate the efficacy of autonomously achieving docking while satisfying stringent terminal constraints on position, velocity, and orientation, demonstrating the framework’s robustness and practical applicability to on-orbit servicing missions.

This article presents a robust control framework to enable dynamic docking of robotic floating satellite platforms actuated by multiple thrusters, ensuring safety while maintaining feasibility. Safety during docking is guaranteed through the integration of adaptive control barrier function (CBF) constraints. Unlike existing switching-based CBF formulations for docking, the proposed approach introduces a CBF that continuously adapts according to the Euclidean distance between the chaser and the target, enabling smoother and less conservative safety enforcement. Furthermore, the adaptive CBF formulation reduces constraint conservatism when necessary to ensure feasibility under thruster input limitations. A tube-based nonlinear model predictive control scheme is developed to achieve robust docking with a moving target under input and CBF constraints. Robustness to bounded disturbances is ensured through a Lyapunov-based invariant tube, which guarantees bounded tracking errors. The efficacy of the proposed framework is demonstrated through software-in-the-loop Gazebo simulations and real-time hardware experiments, achieving docking under on/off actuation and in the presence of external disturbances.